《線性模型和廣義線性模型（第3版）》是2015年世界圖書出版公司出版的著作，作者是[美] C.R.拉奧（C.Radhakrishna Rao） 。
基本介紹
- 中文名：線性模型和廣義線性模型（第3版）
- 作者：[美] C.R.拉奧（C.Radhakrishna Rao）
- 出版社：世界圖書出版公司
- 出版時間：2015年01月01日
- 頁數：570 頁
- 開本：24 開
- 裝幀：平裝
- ISBN：9787510086342
內容簡介,目錄,
內容簡介
《線性模型和廣義線性模型（第3版）》是著名的統計學家C.R.Rao的專著， 這是擴充修訂的第三版，將新的結果囊括其中，是學習線性模型理論和套用的不可多得的書籍。作者用儘量少的假設講述了線性模型和廣義線性模型。不僅運用了*小二乘理論、也有基於凸損失函式和廣義估計方程的估計和檢驗備擇方法。通過書中的各個章節和附錄，理論研究和實踐套用都包括其中，不僅適用於學生，而且也非常適於研究人員和專家學者。
目錄
Preface to the First Edition
Preface to the Second Edition
Preface to the Third Edition
Introduction
1．1 Linear Models and Regression Analysis
1．2 Plan of the Book
2 The Simple Linear Regression Model
2．1 The Linear Model
2．2 Least Squares Estimat．ion
2．3 Direct Regression Method
2．4 Properties of the Direct Regression Estimators
2．5 Centered Model
2．6 No Intercept Term Model
2．7 Maximum Likelihood Estimation
2．8 Testing of Hypotheses and Confidence Interval Estimation
2．9 Analysis of Variance
2．10 Goodness of Fit of Regression
2．11 Reverse Regression Method
2．12 Orthogonal Regression Method
2．13 Reduced Major Axis Regression Method
2．14 Least Absolute Deviation Regression Method
2．15 Estimation of Parameters when X Is Stochastic
3 The Multiple Linear Regression Model and Its Extension
3．1 The Linear Model
3．2 The Principle of Ordinary Least Squares （OLS）
3．3 Geometric Properties of OLS
3．4 Best Linear Unbiased Estimation
3．4．1 Basic Theorems
3．4．2 Linear Estimators
3．4．3 Mean Dispersion Error
3．5 Estimation （Prediction） of the Error Term ε and σ2
3．6 Classical Regression under Normal Errors
3．6．1 The Maximum-Likelihood （ML） Principle
3．6．2 Maximum Likelihood Estimation in Classical Normal Regression
3．7 Consistency of Estimators
3．8 Testing Linear Hypotheses
3．9 Analysis of Variance
3．10 Goodness of Fit
3．11 Checking the Adequacy of Regression Analysis
3．11．1 Univariate Regression
3．11．2 Multiple Regression
3．11．3 A Complex Example
3．11．4 Graphical Presentation
3．12 Linear Regression with Stochastic Regressors
3．12．1 Regression and Multiple Correlation Coefficient
3．12．2 Heterogenous Linear Estimation without Normality
3．12．3 Heterogeneous Linear Estimation under Normality
3．13 The Canonical Form
3．14 Identification and Quantification of Multicollinearity
3．14．1 Principal Components Regression
3．14．2 Ridge Estimation
3．14．3 Shrinkage Estimates
3．14．4 Partial Least Squares
3．15 Tests of Parameter Constancy
3．15．1 The Chow Forecast Test
3．15．2 The Hansen Test
3．15．3 Tests with Recursive Estimation
3．15．4 Test for Structural Change
3．16 Total Least Squares
3．17 Minimax Estimation
3．17．1 Inequality Restrictions
……
4 The Generalized Linear Regression Model
5 Exact and Stochastic Linear Restrictions
6 Prediction in the Generalized Regression Model
7 Sensitivity Analysis
8 Analysis of Incomplete Data Sets
9 Robust Regression
10 Models for Categorical Response Variables
References
Index
